Antifungal Drug Concentration Impacts the Spectrum of Adaptive Mutations in Candida albicans

Abstract Invasive fungal infections are a leading global cause of human mortality. Only three major classes of antifungal drugs are widely used, and resistance to all three classes can arise rapidly. The most widely prescribed antifungal drug, fluconazole, disseminates rapidly and reaches a wide range of concentrations throughout the body. The impact of drug concentration on the spectrum and effect of mutations acquired during adaptation is not known for any fungal pathogen, and how the specific level of a given stress influences the distribution of beneficial mutations has been poorly explored in general. We evolved 144 lineages from three genetically distinct clinical isolates of Candida albicans to four concentrations of fluconazole (0, 1, 8, and 64 μg/ml) and performed comprehensive phenotypic and genomic comparisons of ancestral and evolved populations. Adaptation to different fluconazole concentrations resulted in distinct adaptive trajectories. In general, lineages evolved to drug concentrations close to their MIC50 (the level of drug that reduces growth by 50% in the ancestor) tended to rapidly evolve an increased MIC50 and acquired distinct segmental aneuploidies and copy number variations. By contrast, lineages evolved to drug concentrations above their ancestral MIC50 tended to acquire a different suite of mutational changes and increased in drug tolerance (the ability of a subpopulation of cells to grow slowly above their MIC50). This is the first evidence that different concentrations of drug can select for different genotypic and phenotypic outcomes in vitro and may explain observed in vivo drug response variation.


Introduction
The evolution of antifungal drug resistance is a growing global health concern. Invasive fungal infections caused by opportunistic and recently emerged fungal pathogens are associated with high mortality rates and increased healthcare-associated costs, particularly in immunocompromised patients (Patterson 2002;Pfaller 2012;Pfaller et al. 2019). Over 72 million invasive fungal infections are identified globally per year (Pfaller et al. 2019). Candida albicans is the most prevalent causative agent of invasive fungal infections globally and the mortality rate of these infections is incredibly high (20-60%) despite modern antifungal drug treatment regimens (Pfaller et al. 2010;Andes et al. 2016;Pfaller et al. 2019). This antifungal treatment failure is attributed to the remarkable ability of C. albicans to colonize and adapt to diverse niches and antifungal drug concentrations within the host.
Candida albicans is a heterozygous diploid yeast that has a labile genome and exhibits extensive intra-species genetic diversity with an average nucleotide diversity between any two isolates of ∼0.37% Ford et al. 2015;Hirakawa et al. 2015;Ropars et al. 2018). Although there is some evidence of limited meiotic recombination (Ropars et al. 2018), the vast majority of genetic diversity is generated via asexual mitotic recombination (Bennett and Johnson 2003;Lephart and Magee 2006;Selmecki et al. 2006;Forche et al. 2011Forche et al. , 2018Hickman et al. 2013;Ford et al. 2015;Hirakawa et al. 2015;Todd et al. 2019;Todd and Selmecki 2020;Wang et al. 2021;Kukurudz et al. 2022). Up to ∼20% of cells in a population can become polyploid in as little as 8 h when cultured in 10 μg/ml FLC due to multipolar spindle formation and/ or cytokinesis failure (Harrison et al. 2014). These polyploidization events can occur in different fungal species and diverse C. albicans genetic backgrounds (Harrison et al. 2014;Gerstein and Berman 2020). However, the impact of drug concentration on frequency of polyploidization events and the competitive fitness of polyploid cells over short and long timescales in FLC, remain poorly understood (Gerstein and Sharp 2021).
Only three major classes of antifungal drugs have been approved for use in humans: echinocandins, polyenes, and azoles. Globally, the azole drug fluconazole (FLC) is the most frequently prescribed antifungal drug due to its high bioavailability, low cost, and ease of administration. Azole drugs are fungistatic and inhibit the biosynthesis of ergosterol and cause severe membrane stress to the fungal cell. FLC exhibits linear pharmacokinetics and excellent distribution into various tissues and body fluids, reaching a broad range of physiological concentrations. Serum concentrations are dose-dependent, with typical doses of 200-800 mg/day FLC corresponding to serum concentrations of ∼7.5-60.5 μg/ml FLC (Schiave et al. 2018). FLC levels reach peak serum concentration 1-6 h after administration and remain in the system for days (elimination half-life is ∼30 h in individuals with functioning kidneys [Cousin 2003]). Additionally, FLC concentrations vary between different tissues in the body (1 μg/ml to over 22 μg/ml), with the highest concentration of FLC being detected in the spleen (Fischman et al. 1993). Lower doses of FLC are used as prophylaxis for patients undergoing solid tissue transplantation (Felton et al. 2014;Pappas et al. 2016;Schiave et al. 2018) and recurrent vulvovaginal candidiasis (Denning et al. 2018), however higher daily doses of FLC may result in longer survival of patients with candidiasis (Schiave et al. 2018). Why different drug concentration influence treatment success remains largely unknown.
Azole drug resistance arises in clinical settings during antifungal therapy and severely limits subsequent treatment options. Drug susceptibility is determined in the laboratory at 24 h and defined as the minimum inhibitory concentration (MIC) that reduces 50% of growth (MIC 50 ), and drug resistance is the ability to grow in drug concentrations that inhibit susceptible isolates, typically defined by epidemiological cut-off values (Pfaller et al. 2010(Pfaller et al. , 2011. Known mechanisms of azole resistance include the upregulation of drug efflux pumps (ABC family and MFS multidrug efflux pumps), mutations in the gene encoding the azole drug target, Erg11, and mutations that bypass the membrane stress response (Marr et al. 1998;Cowen et al. 2000;Anderson et al. 2003Anderson et al. , 2004Selmecki et al. 2006;Bouchonville et al. 2009;Fothergill et al. 2014;Harrison et al. 2014;Ford et al. 2015;Todd et al. 2019;Todd and Selmecki 2020). Additionally, ∼50% of all FLC-resistant C. albicans isolates contain at least one aneuploid chromosome ) and chromosomal instability, in general, can increase the frequency of FLC-resistant cells (Brimacombe et al. 2019;Yang, Todd, et al. 2021). One specific segmental aneuploidy, isochromosome 5L (i(5L)), causes drug resistance via an increase in the copy number of ERG11 and TAC1 (Selmecki et al. , 2008. i(5L) can arise rapidly under FLC selection, occurs in diverse genetic backgrounds of C. albicans, and frequently results in multi-azole resistance (Selmecki et al. 2008. In addition to azole resistance, azole tolerance (defined as the ability of a drug-susceptible isolate to grow slowly in drug concentrations above the MIC 50 beyond 24 h) also has major implications in clinical settings for fungistatic drugs that metabolically inhibit, rather than kill, susceptible cells (Berman and Krysan 2020). Fungal drug tolerance is linked to azole treatment failure and the inability to clear an infection, despite these isolates being considered drug-sensitive by the typical MIC 50 assays (Sanglard et al. 2003;Delarze and Sanglard 2015;Rosenberg et al. 2018;Berman and Krysan 2020). Currently, it is thought that antifungal drug tolerance occurs via enhanced signaling of cellular stress response pathways including modulation of the calcium signaling pathway, nutrient detection, and HSP90 activation (Cowen and Steinbach 2008;Rosenberg et al. 2018;Murphy and Bicanic 2021). Drug-tolerant fungal cells are often present as a distinct subpopulation and can evolve independently of drug resistance, existing alongside drug-resistant or susceptible cells (Gerstein and Sethi 2022). Tolerance in fungi seems to be a stable characteristic and isolates that evolve increased tolerance do not change in the prolonged absence of FLC (Rosenberg et al. 2018). Notably, tolerance has distinct definitions in the bacterial and fungal communities (Westblade et al. 2020;Michaux et al. 2022). As an example, FLC-tolerant Candida do not exhibit the slowed growth phenotype that tolerant bacterial cells exhibit in the absence of drug (Rosenberg et al. 2018;Todd and Selmecki 2020;Michaux et al. 2022). Intriguingly, our recent experiments demonstrate that azole tolerance and cross-tolerance to different azole drugs can evolve rapidly in vitro (Todd and Selmecki 2020;Kukurudz et al. 2022), yet the mechanisms that distinguish drug-resistant and drug-tolerant phenotypes in fungi are not fully characterized.
Experimental evolution provides an opportunity to pinpoint the order of events leading to antifungal drug resistance and drug tolerance, the degree of parallelism among adaptive mutations between different genetic backgrounds and different environments, and the phenotypic effect of mutations acquired during adaptation. Prior studies into how antifungal drugs impact the spectrum of mutations observed during adaption primarily focused on increasing FLC concentrations or on short-term evolution experiments in a single concentration of FLC (Cowen et al. 2000; Anderson et al. 2003; Mount et al. 2018; Rybak et al. Todd et al. · https://doi.org/10.1093/molbev/msad009 MBE 2020; Burrack et al. 2022). In one example, six lineages from one C. albicans strain were maintained at increasing concentrations of FLC for 300-400 generations, where the MIC 50 was quantified every 10-20 generations and the drug concentration was increased to twice the MIC 50 , to a maximum concentration of 128 μg/ml FLC (Cowen et al. 2000). In a similar example, three lineages from one genetic background of haploid S. cerevisiae were exposed to increasing concentrations of FLC over the span of 400 generations, starting at 16 μg/ml FLC and increasing every 100 generations to 32 μg/ml, 64 μg/ml, and 128 μg/ml FLC (Anderson et al. 2003). Although these and other evolutionary studies provided valuable insight into mechanisms that drive azole resistance, little is known about how prolonged exposure to a constant drug concentration impacts evolutionary trajectories and what distinguishes selection for azole resistance from azole tolerance.
Overall, the impact of genetic and environmental factors, including FLC concentration, on the acquisition of drug resistance and tolerance phenotypes is not known. Here, we provide the first comprehensive analysis of how three different clinical isolates of C. albicans adapt to different physiological concentrations of FLC using a single standardized methodology. We characterized the phenotypic responses and mutational spectrum (single-nucleotide polymorphisms, aneuploidy, segmental aneuploidy, and whole-genome ploidy changes) at four different drug concentrations during adaptation of C. albicans in vitro. We first identified the spectrum and effect of mutations acquired in two different genetic backgrounds with the same starting MIC (0.5 μg/ml) and found that drug concentrations near the starting MIC selected for increases in the frequency of segmental aneuploidies and increases in resistance (MIC). Higher drug concentrations (supra-MIC) selected for increases in drug tolerance, but only rarely increased resistance. We then quantified the spectrum and effect of mutations after adaptation to the same four drug concentrations in a third genetic background that had a higher starting MIC (8 μg/ml). Strikingly, all lineages derived from this genetic background acquired trisomy of chromosome 5 and a concomitant increase in MIC during adaptation to the 8 μg/ml environment, but not during adaptation to lower or higher drug concentrations. These results identify that distinct drug response phenotypes are under selection at different drug concentrations and provide new evidence for consideration of initial MIC when treating challenging fungal infections.

High Concentrations of Fluconazole Select for Drug Tolerance Phenotypes, low Concentrations Select for Resistance
To determine how C. albicans adapts to different physiologically relevant concentrations of FLC, we first compared two genetically distinct progenitors with the same initial MIC 50 (SC5314 and P75063, MIC 50 = 0.5 μg/ml FLC). Twelve single colonies from each progenitor were selected for parallel evolution experiments (SC5314: single colonies labeled A-L; P75063: single colonies labeled M-X), grown up in rich medium overnight and then split four ways into the following treatment lineages: 0 μg/ml FLC, 1 μg/ml FLC, 8 μg/ml FLC, and 64 μg/ml FLC (e.g., single colony A was divided into lineages A 0 , A 1 , A 8 , and A 64 ). All 96 lineages were serially passaged every 72 h into fresh medium using a 1:1000 dilution. After 10 passages (∼100 generations) all 96 lineages underwent phenotypic analysis, and 48 lineages were selected for whole-genome sequencing prior to phenotypic analysis.
We measured drug resistance (MIC 50 at 24 h, abbreviated as MIC) and drug tolerance (Supra-MIC 50 Growth, SMG, at 48 h) from all evolved lineages using a liquid microbroth dilution assay. MIC was quantified as the concentration of FLC that decreased the OD 600 of the culture by ≥50% when compared with the no-drug control and SMG was calculated by taking the average OD 600 value of the wells above the MIC 50 at 48 h and dividing this average by the OD 600 in the no-drug control well at 48 h (see Materials and Methods). All the FLC-evolved lineages acquired an increase in MIC and/or SMG relative to their progenitor ( fig. 1 1A and B, P < 0.05, Kruskal-Wallis with Dunn's multiple comparison). In contrast, lineages evolved in 8 and 64 μg/ml FLC tended to acquire significantly higher tolerance than lineages evolved in either 0 or 1 μg/ml FLC ( fig. 1C and D, P < 0.05, Kruskal-Wallis with Dunn's multiple comparison). Resistance and tolerance levels were not significantly different between the lineages evolved in 8 and 64 μg/ml FLC, likely indicating that these two environments influenced the C. albicans populations similarly. These phenotypic results indicate that adaptation to different drug concentrations significantly influences the phenotypic trajectory of adaptation.

Frequent Polyploidization Events are Selected for During Adaptation to Fluconazole
To determine what genotypic changes underlie the phenotypic differences at each drug concentration, we performed comprehensive comparative genomics using flow cytometry and whole-genome sequencing. Flow cytometry quantifies total DNA content by measuring fluorescence after staining with propidium iodide. Lineages with a range of both ploidy and aneuploidy levels are detected by an increase or decrease in fluorescence relative to the diploid progenitor strain ( fig. 2A) . All 0 μg/ml FLC evolved lineages remained diploid ( fig. 2B and C, Table 2), whereas FLC-evolved lineages exhibited a significant increase in genome size (P < 0.05, Kruskal-Wallis with Dunn's multiple comparison). These results indicate that karyotypic changes occurred at all three drug Evolution of Antifungal Resistance or Tolerance is Dependent on Drug Concentration · https://doi.org/10.1093/molbev/msad009MBE concentrations, though the degree of genome size increase was influenced by strain background.
To determine if polyploidization (i.e., evolved a base ploidy of ∼3N or 4N) correlated with resistance or tolerance phenotypes, we compared the median genome size with the MIC and SMG values from figure 1. We found that there was no significant correlation between increasing genome size and MIC or SMG in either strain background for any drug concentration ( fig. 2D and E, Linear regressions Table 2-Tab 2). We performed growth curve analysis on the lineages with the highest ploidy levels to better understand how they reached fixation. All lineages tested had significantly improved growth in 1 μg/ml FLC compared with the diploid progenitors, and in the absence of drug only some SC5314-derived polyploid lineages had a small fitness cost (supplementary fig. S2, Supplementary Material online). In summary, all evolved lineages have increased their ability to respond to drug in the presence of FLC, but the degree of genome size increase is not differentially driving increases in MIC and SMG.

Segmental Aneuploidies are Fluconazole Concentration-dependent
To determine the full spectrum of mutations that arose during the evolution experiment and to provide additional mechanistic insight into adaptation beyond ploidy changes, populations evolved in all four drug concentrations from six lineages from each progenitor (e.g., A 0 , A 1 , A 8 , A 64 ; B 0 , B 1 , B 8 , B 64 , etc.) were selected for whole-genome sequencing (48 lineages in total). All 12 of the lineages evolved in 0 μg/ml FLC remained euploid by chromosome copy number analysis. In contrast, aneuploidy was detected in 35/36 of the FLC-evolved lineages ( fig. 3A and B; only lineage S 64 remained euploid diploid). Amplification of Chromosome R, containing the ribosomal DNA array, was the most common aneuploidy identified at both 8 and 64 μg/ml FLC. Most lineages contained multiple aneuploid chromosomes, and lineages derived from SC5314 had nearly four times the number of wholechromosome aneuploidy events than the lineages derived from P75063 at both 8 and 64 μg/ml FLC ( fig. 3C). This suggests that ploidy analysis by flow cytometry may be underestimating the frequency of chromosome copy number changes, that are more common than polyploidization, in the SC5314 background.
Segmental aneuploidies that amplified only a portion of a chromosome occurred almost exclusively in the lineages evolved at 1 μg/ml FLC ( fig. 3D, 5/6 lineages from both progenitors). Amplification of the left arm of Chromosome 5 in an isochromosome structure (i(5L)) FIG. 1. SC5314-and P75063-derived lineages exposed to 1 μg/ml FLC had a significant increase in MIC, whereas lineages grown in either 8 μg/ml or 64 μg/ml FLC had a significant increase in tolerance. MIC measured at 24 h for each of the 48 replicate lineages of (A) SC5314 and (B) P75063. Median MIC values for each treatment group (diamonds) and of the FLC-sensitive progenitors (dashed line) are indicated. Groups not sharing any letter are significantly different (P < 0.05, Kruskal-Wallis with Dunn's multiple comparison). Supra-MIC Growth values (SMG) measured at 48 h for each of the 48 replicate lineages of (C ) SC5314 and (D) P75063. Median SMG values for each treatment group (diamonds) and of the FLC-sensitive progenitors (dashed line) are indicated. Groups not sharing any letter are significantly different (P < 0.05, Kruskal-Wallis with Dunn's multiple comparison). All MIC and SMG values represent three biological replicates. Todd et al. · https://doi.org/10.1093/molbev/msad009  MBE was the most frequent segmental aneuploidy in both genetic backgrounds (SC5314: 5/6 lineages, P75063: 2/6 lineages). This is the first report of i(5L) formation in the reference strain SC5314 and the first indication that drug concentration can impact selection for, and possibly formation of, this recurrent segmental aneuploidy. Five additional segmental aneuploidies of Chromosomes 1, 3, and 4 amplified from 3 to 13 copies per genome in P75063 lineages evolved in 1 μg/ml FLC ( fig. 3B; supplementary figs. S3 and S4, Supplementary Material online). The copy number breakpoints of all segmental aneuploidies occurred at long repeat sequences as described previously (Todd et al. 2019;Todd and Selmecki 2020). Only one segmental aneuploidy was identified above 1 μg/ml FLC (Lineage J 64 ) and occurred at the rDNA array on ChrR, a common copy number breakpoint in clinical isolates. The general lack of segmental aneuploidies observed at 8 and 64 μg/ml is surprising, especially given the frequency of whole-chromosome aneuploid events observed at these drug concentrations. We then quantified LOH events across all lineages. Ten LOH events were detected in seven of the 48 lineages, including whole-chromosome LOH events (5/10) and segmental chromosome LOH events (5/10) ranging from ∼8 kb to ∼716 kb (Table 3). LOH events occurred almost exclusively in the lineages evolved at 1 μg/ml FLC (9/10 LOH events). Most of the LOH events occurred in SC5314 (7/10) compared with P75063 (3/10). The segmental chromosome LOH events frequently occurred at long inverted repeat sequences similar to the copy number breakpoints previously implicated in FLC adaptation (Todd et al. 2019). In two different SC5314 lineages, B 1 and D 1 , LOH of all or part of the right arm of Chr5 was associated with amplification of the left arm of Chr5 in an i(5L) isochromosome. Therefore, the inverted repeat sequence flanking the centromere of Chr5 was involved in both copy number variation and LOH ). Additionally, whole-ChrR LOH was found in both progenitors at 1 μg/ml, SC5314 J 1 and P75063 P 1 .

MBE
In addition to DNA copy number and LOH events, we determined the spectrum of SNVs in coding sequences from each lineage. We identified 57 and 69 high confidence de novo SNVs that reached allele frequencies of 5-100% in the SC5314-and P75063-derived lineages ( Table 3). The greatest number of SNVs were in the SC5314 no drug-evolved lineages (33/57, fig. 3E) and the P75063 1 μg/ml FLC-evolved lineages (28/69, fig. 3F). A majority of all SNVs resulted in nonsynonymous substitutions (30/57 SNVs from SC5314; 45/69 SNVs from P75063). Of the FLC-evolved lineages, more SNVs were acquired at 1 μg/ml than in the other drug concentrations, regardless of genetic background. To ask if any gene functions were enriched within the genes harboring SNVs from all FLC-evolved lineages (1, 8, and 64 μg/ml FLC) we performed gene ontology (GO) analysis. The cellular process "long-chain fatty acid metabolic process" (encompassing genes ACC1, CTF1, and POX1-3) was the only GO term significantly enriched for the FLC-evolved lineages (P < 0.05, hypergeometric distribution with Bonferroni Correction).
Next, we filtered for de novo alleles that reached high frequency in each lineage that might explain the evolved phenotypes. For example, the diploid Lineage E 1 evolved a 4-fold increase in MIC and acquired only one missense allele ECM25 Ser467Asn at a frequency of ∼54%. ECM25 encodes a protein involved in cell wall biosynthesis, cell separation and morphogenesis in C. albicans and the S. cerevisiae ortholog is required for stress-induced cell elongation (Zhang et al. 2008). Lineage E 1 also acquired multiple aneuploidies of i(5L), Chr3, and Chr7, however, so future work is needed to determine which mutations (alone or in combination) are beneficial. Only three nonsense alleles were identified, in YAK1 Tyr385* (P75063-R 8 , 22% frequency), DUT1 Gln56* (SC5314-D 64 , 18%), and DOT1 Glu127* (P75063-Q 1 , 10%). YAK1 encodes a serine-threonine protein kinase and inhibition of Yak1 was recently shown to prevent filamentation in C. albicans (MacAlpine et al. 2021), which may provide these cells with adaptive benefit in the in vitro evolution experiment where filamentation is not required. Ultimately, linking putative causal mutations to the observed phenotypes will require additional experiments that take the effect of aneuploidy and polyploidy into account as well. Intriguingly, no SNVs were detected in genes known to cause drug resistance in C. albicans. This is in stark contrast to the narrow and recurrent SNVs identified in haploid fungal species like Saccharomyces cerevisiae, Candida glabrata, and Candida auris during adaptation to similar FLC concentrations (Anderson et al. 2003(Anderson et al. , 2004Rybak et al. 2020;Ksiezopolska et al. 2021;Burrack et al. 2022). Although no identical SNVs arose independently in different lineages, several genes acquired SNVs in different lineages (RIM101, DAL5, RGD3, PXP2, TERT, orf19.3604, orf19.6457, and orf19.6970). However, many of these SNVs encoded synonymous mutations, including a missense and synonymous SNV in RIM101 from lineage P75063-T 64 and SC5314-A 1 . The overall pattern is that polyploidy, aneuploidy, and segmental aneuploidy is likely a faster route to adapting to FLC in diploid C. albicans isolates and these karyotypic mutations are more likely to repeatedly arise and be selected independently in different lineages than rare adaptive point mutations, at least in the early stages of FLC exposure (Yang, Todd, et al. 2021;Gerstein and Sethi 2022).
In summary, drug concentration dramatically impacts both the phenotypic and genotypic basis of adaptation of lineages from two diverse genetic backgrounds of C. albicans evolved for 100 generations. We rationalized that this was due to the relative stress imposed on the cells rather than an inherent property of the specific drug concentration itself, as the two progenitors have the same initial MIC (0.5 μg/ml). We therefore hypothesized that a different progenitor with a higher initial FLC MIC would also acquire a unique mutational signature at a drug concentration near its initial MIC compared with other drug concentrations.

Mutational Spectrum and Adaptive Potential are Impacted by Initial Fitness in Fluconazole
To test whether a higher initial FLC MIC would alter the spectrum of adaptive mutations, we evolved lineages from clinical isolate FH1, which has an initial FLC MIC of 8 μg/ml (Marr et al. 1997(Marr et al. , 1998(Marr et al. , 2001. Importantly, isolates with an MIC ≥ 8 μg/ml are defined as clinically resistant due to statistically increased treatment failures (Pfaller et al. 2010(Pfaller et al. , 2011, however why treatments fail is poorly understood. We performed identical in vitro evolution experiments as described above. Resistance (MIC) and tolerance (SMG) assays were conducted as previously described. No changes in MIC or SMG were observed at 0 μg/ml and 1 μg/ml FLC. Strikingly, the lineages evolved in 8 μg/ml FLC acquired a significantly higher MIC than the three other treatment groups ( fig.  4A, supplementary fig. S5, Supplementary Material online, P < 0.05, Kruskal-Wallis with Dunn's multiple comparison test). Median SMG was minimally but significantly increased in both the 8 μg/ml and 64 μg/ml FLC lineages relative to the 0 μg/ml FLC and 1 μg/ml FLC lineages. This is in sharp contrast to lineages evolved from the other two progenitors that acquired strong tolerance phenotypes at drug concentrations well above their initial MIC and may indicate that adaptation via tolerance is less accessible to this progenitor.
Ploidy analysis and whole-genome sequencing were performed on all 12 FH1 lineages from all four treatment conditions (48 total). All FH1-evolved lineages remained diploid (Table 2), consistent with recent ploidy analysis of FH1 after evolution to 1 μg/ml FLC (Gerstein and Berman 2020). Strikingly, trisomy of Chr5 was observed in all 12 lineages evolved in the presence of 8 μg/ml FLC ( fig. 4B). Additionally, all 12 lineages acquired an extra copy of the same Chr5 homolog, Chr5B. In the FH1 progenitor, the Chr5B homolog contains a beneficial allele of TAC1 (TAC1-7), and amplification of this homolog was previously observed in an FH1 isolate obtained from an agar plate containing 10 μg/ml FLC (Coste et al. 2006). Two segmental aneuploidies on Chr7 and ChrR were detected at low frequency in multiple evolved lineages from the 0, 1, and 64 μg/ml FLC groups ( fig. 4B). These segmental aneuploidies were likely present in some of the initial single colony lineages and did not correlate with changes in MIC or SMG. Finally, no LOH was detected in any of the FH1-evolved lineages.
In addition to chromosome amplification, we also identified 38 high confidence de novo SNVs that reached allele frequencies of 5-100% within coding sequences across all FH1 lineages (Table 3). The greatest number of SNVs per treatment was in the 8 μg/ml FLC lineages ( fig. 4C). Therefore, lineages derived from all three progenitors (FH1, SC5314, and P75063) acquired the most SNVs during adaptation to the drug concentration that was closest to their initial MIC. Only two genes (ALS2 and TLO9) were mutated in different lineages from FH1 or in combination with the SC5314 and P75063 lineages, and both genes represent large gene families. Together, these findings indicate that strain background can significantly influence adaptation, with the initial MIC relative to the environment impacting both mutational spectrum and evolutionary trajectory during FLC treatment.

Discussion
Higher daily doses of FLC have resulted in longer survival of patients with candidiasis (Schiave et al. 2018). Why this is, Todd et al. · https://doi.org/10.1093/molbev/msad009 MBE and how isogenic C. albicans lineages adapt to different physiological concentrations of FLC within host niches remains largely unknown. In this study, we conducted 144 parallel in vitro evolution experiments to examine the impact of drug concentration on the genotypic and phenotypic basis of adaptation. We found that drug concentration dramatically impacts both drug response phenotypes (resistance or tolerance) and the spectrum of mutations acquired across three different genetic backgrounds. In general, concentrations of FLC that were at or two times above the MIC (near-MIC) of the progenitor selected for lineages that have significantly increased drug resistance, whereas higher concentrations of FLC (supra-MIC) selected for lineages with significantly increased drug tolerance. The acquisition of recurrent and distinct whole-chromosome and segmental aneuploidy was extremely prevalent in drug concentrations near the initial MIC, with the specific evolved karyotype linked to both progenitor strain and drug environment. Adaptation to FLC did not occur in either the absence of drug or in drug concentrations below that of the progenitor's starting MIC. These findings highlight that the initial MIC of a clinical isolate can dramatically alter how the isolate adapts to FLC and that different concentrations of the same drug select for different evolutionary trajectories. Specifically, we observed that selection seems to act either to increase FLC resistance or FLC tolerance, suggesting phenotypic improvement in these traits represents distinct peaks on the fitness landscape. These findings have broad implications for antifungal drug therapies and clinical best practices and could underlie why some treatment regimens fail. Current and future screens for novel antifungal drugs should take multiple drug concentrations into effect to assess efficacy and to understand how differing concentrations may impact fitness outcomes and potential treatment failure.
We found that lineages from three progenitors evolved in near-MIC concentrations of FLC increased in resistance to FLC. Lineages from all three progenitors exposed to supra-MIC concentrations significantly increased their tolerance to FLC, though the degree of tolerance was much lower in the third progenitor (FH1, which has an ancestrally higher MIC). We did not identify a correlation between genome size, appearance of aneuploidies, or SNVs in specific genes and the tolerance of a lineage, indicating that many different genotypes or epistatic interactions may drive the drug response phenotypes. The rapid increase in tolerance (but not resistance) at supra-MIC levels, as well as a lack of correlation with evolved genome size is consistent with a recent evolution study that evolved lineages of C. albicans to supra-MIC levels of the azole Posaconazole (Kukurudz et al. 2022). Although the drivers of antifungal drug tolerance remain largely unknown, genes involved in core stress responses likely play a role (Cowen et al. 2014;Rosenberg et al. 2018;Berman and Krysan 2020). Cells exposed to supra-MIC concentrations of antifungal drug may be able to slow growth and division enough to preserve viability, whereas lower concentrations of antifungal drugs may still allow cells to progress through the cell cycle leading to the acquisition of segmental aneuploidy or point mutations that result in bona fide resistance. A small number of evolved lineages acquired both high tolerance and high resistance (e.g., SC5314-G 1 and P75063-N 8 ) and will be valuable for future work that aims to tease apart the molecular mechanism driving both phenotypes.
Karyotypic variation (i.e., whole chromosome, isochromosome, and segmental aneuploidy) were observed in all three different progenitor backgrounds following FLC evolution. By comparing multiple drug concentrations, we found that a different suite of genomic changes occurred when C. albicans was evolved to FLC concentrations near the initial MIC of the progenitor strains, compared with concentrations above the MIC. We propose that the observed differences in evolved genotype are due to the relative stress on the cells rather than an inherent property of the specific drug concentration. Our results suggest that the critical distinction is not drug concentration per se, but a physiological breakpoint where cells experience one degree of stress near their initial MIC, and a different degree of stress below and above their initial MIC.
Whole-chromosome aneuploidy of Chr3, Chr5, Chr6, and ChrR was the most common across all evolved lineages. Aneuploidy (whole and partial chromosome) has been observed in most fungal pathogens, including in isolates obtained directly from patients and/or during experimental evolution in the presence of antifungal drugs (Marichal et al. 1997;Sionov et al. 2010;Ngamskulrungroj et al. 2012;Demers et al. 2018;Ksiezopolska et al. 2021;Yang, Lu, et al. 2021;Burrack et al. 2022). Some aneuploidies were more common from some progenitor strains and in response to some environments. The most striking example of this phenomenon was the increase in MIC and recurrent amplification of Chr5B in all 12 lineages derived from FH1 during adaptation to 8 μg/ml FLC ( fig. 4), which was not observed during adaptation to lower or higher concentrations of drug in FH1. This suggests that there may be a fitness tradeoff to the beneficial effects of Chr5B aneuploidy in the FH1 background at both lower and higher concentrations of FLC. FH1 is the first in a series of isolates obtained from a bone marrow transplant patient before initiation of antifungal therapy including FLC (Marr et al. 1997(Marr et al. , 1998. Later isolates from this patient (FH2-FH9) are related to FH1 and several independently acquired amplification of Chr5B on an isochromosome or homozygosis of the TAC1-7 allele on Chr5B (Coste et al. 2006;Selmecki et al. 2006Selmecki et al. , 2008Abbey et al. 2014). Furthermore, both Chr5A and Chr5B aneuploidy was observed in SC5314 and P75063 lineages evolved in different drug concentrations. Finding extremely parallel aneuploidy is exciting from a clinical viewpoint. An "evolutionary trap" approach to extend the life of existing antifungal drugs was proposed by Rong Li and colleagues where treatment with a single antifungal drug selects for a genotype that can be targeted by a secondary drug. Their screen Evolution of Antifungal Resistance or Tolerance is Dependent on Drug Concentration · https://doi.org/10.1093/molbev/msad009MBE identified the FDA-approved drug pyrvinium that caused increased killing of C. albicans cells that had an i(5L) aneuploidy compared with wildtype cells (Chen et al. 2015). Our data support that this evolutionary trap may be incredibly effective at near-MIC FLC concentrations, where we observed recurrent alterations of Chr5 in all three genetic backgrounds.
In addition to the isochromosome of Chr5, segmental aneuploidy on Chr1, Chr3, and Chr4 was identified in six lineages from P75063. These segmental aneuploidies consistently amplify large regions of a chromosome and can form via an unstable dicentric chromosome that progresses through successive rounds of breakage-fusion-bridge cycles that are repaired via nonallelic homologous recombination between long inverted repeat sequences (Todd and Selmecki 2020). Several of these segmental aneuploidies were shown to be sufficient to confer FLC resistance (Selmecki et al. 2008Todd et al. 2019). The experiments here are the first to clarify that segmental aneuploidies recurrently and predominantly form only at FLC concentrations that are near the MIC of the original progenitor isolate, and furthermore suggest that the propensity to acquire segmental aneuploidy is background-dependent. We also found that drug concentration impacts the frequency of i(5L) formation. i(5L) was only observed in lineages evolved in 1 μg/ml FLC from progenitor SC5314 (the C. albicans reference strain; 5/6 lineages) and P75063 (2/6 lineages). Interestingly, the centromere-specific histone H3 variant Cse4/CENP-A is depleted from the centromere during growth in 10 μg/ml FLC, which increases the rate of chromosome missegregation in the SC5314 background (Brimacombe et al. 2019). Therefore, it is tempting to speculate that at low concentrations of FLC (1 μg/ml), Cse4 binding is still sufficient to promote dicentric chromosome formation and breakage-fusion-bridge cycles that can promote segmental aneuploidies, but at higher FLC concentrations, including 8 μg/ml, 10 μg/ml, and 64 μg/ml FLC, centromeres are more destabilized and whole-chromosome aneuploidy and polyploidization are observed more frequently.
In addition to finding the evolution of distinct aneuploidies, at all drug concentrations we also found multiple lineages from SC5314 and P75063 where polyploid cells . Median genome copy number was estimated as the first (G1) propidium iodide (PI) peak that contained >10% of the total population of cells. Dashed horizontal lines indicate the 2C, 3C, and 4C genome copy numbers based off the SC5314 and P75063 progenitor genome size. There is a significant increase in median genome size for the FLC-evolved lineages from SC5314 (P < 0.05, Kruskal-Wallis with Dunn's multiple comparison) and P75063 (P < 0.05, Kruskal-Wallis with Dunn's multiple comparison). There is a significant increase in median genome size between lineages derived from SC5314 and P75063 for the 8 μg/ml treatment group (P < 0.01, Mann-Whitney U test) and for the 64 μg/ml treatment group (P < 0.01, Mann-Whitney U test). Asterisk above graph indicates significant differences compared with the 0 μg/ml treatment group (P < 0.05 Kruskal-Wallis with Dunn's multiple comparison). (D) MIC and (E) SMG measurements from figure 1 by genome copy number, faceted by each progenitor and evolution treatment. Median genome copy numbers (2C, 3C, 4C) are the same as above. Lineages with an MIC >256 μg/ml FLC were excluded from the SMG plot. Linear regressions for each panel were conducted, with no significant correlations (   MBE swept the population within 100 generations of evolution. In C. albicans, acute treatment (8 h) with 10 μg/ml FLC can induce polyploidization in ∼20% of cells in a population (Harrison et al. 2014). These polyploid "timera" cells form after failed cytokinesis and can give rise to highly aneuploid daughter cells with increased MICs (Harrison et al. 2014). Likewise, Cryptococcus neoformans polyploid "titan" cells exposed to FLC rapidly produced highly aneuploid daughter cells with increased fitness in the presence of FLC (Gerstein et al. 2015). In a large-scale parallel in vitro evolution experiment, 20 diverse C. albicans clinical isolates were evolved for 100 generations in a single concentration of FLC (1 μg/ml) (Gerstein and Berman 2020). In parallel to results here, changes in genome size were pervasive in all backgrounds except for those whose initial MIC was higher than 1 μg/ml (Gerstein and Berman 2020). Here we found that FH1 remains diploid at all drug concentrations tested, whereas polyploidization occurred more frequently in P75063 lineages than in SC5314 lineages ( fig. 2). This is in contrast to whole-chromosome aneuploidy, where SC5314 lineages had nearly four times the number of aneuploidy events than P75063. Aneuploid chromosomes in SC5314 may be a result of transient polyploidization followed by concerted chromosome loss events resulting in highly aneuploid cells (Bennett and Johnson 2003;Hickman et al. 2015;Gerstein et al. 2017;Avramovska and Hickman 2019). Polyploidization can have significant impact on the rate and dynamics of subsequent adaptive events, including acquisition of beneficial point mutations and aneuploid chromosomes (Scott et al. 2017). S. cerevisiae polyploid cells acquire significantly more point mutations, segmental, and wholechromosome aneuploidies than diploid cells during adaptation to low carbon environment (Selmecki et al. 2015;Scott et al. 2017). Additionally, the fitness effect of a given mutation, including aneuploidy, can change with polyploidy and can reveal beneficial effects that do not provide a similar benefit to isogenic diploids (Selmecki et al. 2015).
Using whole-genome sequencing we also found polyploidy was frequently associated with chromosome aneuploidy, and interestingly, all the polyploid isolates that we randomly selected for sequencing contained amplification of ChrR ( fig. 3A and B). Further analysis is needed of the trajectory of polyploid cells over the course of evolution. Surprisingly, no SNVs were observed in well-known drug resistance factors in the timeframe of our experiments with initially diploid C. albicans. During adaptation to FLC in vitro, haploid yeast species including S. cerevisiae, C. glabrata, and C. auris acquired mutations that are recurrent and narrow in spectrum, including mutations in PDR1, ERG3, ERG11, UPC2, TAC1, MDR1, CDR1, CDR2 (Anderson et al. 2003(Anderson et al. , 2004Rybak et al. 2020;Ksiezopolska et al. 2021;Burrack et al. 2022). The rate and spectrum of acquired point mutations is impacted by cellular ploidy in many environments through dominance as well as differences in effect size (Gerstein et al. 2006;Gerstein 2013;Selmecki et al. 2015;Buskirk et al. 2017;Scott et al. 2017;Fisher et al. 2018;Marad et al. 2018). Elegant bulksegregant fitness analysis in S. cerevisiae found that diploid populations contain fewer driver mutations and more FIG. 3. Fluconazole concentration impacts the mutational spectrum of evolved lineages. Whole-genome sequence data plotted as the log2 ratio and converted to chromosome copy number (y-axis, 1-8 copies) as a function of chromosome position (x-axis, Chr1-ChrR) using the Yeast Mapping Analysis Pipeline (YMAP; [Abbey et al. 2014]). The baseline chromosome copy number (ploidy) was determined by flow cytometry (see Materials and Methods, and fig. 2). Lineages of (A) SC5314 and (B) P75063 are grouped by drug treatment (0 μg/ml FLC, 1 μg/ml FLC, 8 μg/ ml FLC, and 64 μg/ml FLC). Gray shading indicates heterozygous positions throughout the genome, which are distinct between the two progenitors, with darker gray regions containing more heterozygous loci and white regions containing few or no heterozygous loci. Centromere position indicated by a notch on every chromosome. Dots below the bottom YMAP of each drug treatment group identifies the location of the Major Repeat Sequences (MRS) and the ribosomal DNA array (rDNA). Histogram of (C) whole-chromosome aneuploidy events and (D) segmental aneuploidy events detected by read depth analysis of lineages derived from SC5314 (black bars) and P75063 (blue bars). Segmental aneuploidies predominantly occur at 1 μg/ml FLC for lineages derived from both progenitor isolates. Frequency and type of de novo single-nucleotide variants identified in the 48 replicate lineages of (E) SC5314 and (F ) P75063.  Evolution of Antifungal Resistance or Tolerance is Dependent on Drug Concentration · https://doi.org/10.1093/molbev/msad009MBE        Evolution of Antifungal Resistance or Tolerance is Dependent on Drug Concentration · https://doi.org/10.1093/molbev/msad009MBE    Evolution of Antifungal Resistance or Tolerance is Dependent on Drug Concentration · https://doi.org/10.1093/molbev/msad009MBE  hitchhiker mutations relative to haploid populations evolved in the same environment, and that all beneficial mutations in diploids were dominant or overdominant (Aggeli et al. 2021). Determining the impact of C. albicans ploidy on the rate and mechanism of adaptation to different drug concentrations may be possible in the future, including a direct comparison of isogenic haploid, diploid and tetraploid C. albicans, however stable haploid and tetraploid lineages of C. albicans currently do not exist (Hickman et al. 2015;Selmecki et al. 2015).

Future Directions
Available antifungal drugs are limiting Perfect et al. 2022), and it is critical to understand the mechanisms by which resistance and tolerance evolve. Considerable effort has been extended to characterize genic mutations. The same effort has not yet been extended to understanding the mechanisms that underlie aneuploidy-associated antifungal resistance, despite the observed high frequency of aneuploidy in clinical and experimental fungal isolates. We previously showed that the gene copy numbers of ERG11 and TAC1 on the left arm of Chr5 are sufficient for FLC resistance in an i(5L) strain, and there is a linear correlation between their combined gene copy-numbers and FLC MIC (Selmecki et al. 2008). For other aneuploidies the mechanism is less clear. In general, aneuploidy alters cell physiology in ways that may promote antifungal tolerance or resistance. Aneuploid budding yeast cells exhibit increased plasmamembrane stress and impaired endocytosis that may alter metabolic and proteomic homeostasis leading to altered fitness states during periods of cellular stress (Torres et al. 2007;Pavelka et al. 2010;Tsai et al. 2019). Future studies are needed to comprehensively determine which gene(s) on an amplified chromosome are under selection across diverse genetic backgrounds/fungal species. Development of CRISPR tools that amplify gene expression of every gene on an aneuploid chromosome or region will help determine what genes in an amplified region are under selection during antifungal treatment (Uthayakumar et al. 2020). These molecular tools may further reveal the mechanisms that are under selection at specific drug concentrations, and in different genetic backgrounds, including allele-specific phenotypes that are under selection in these distinct genetic backgrounds.

Yeast Strains and Culture Conditions
All strains used in this study are described in Table 1. Strains were stored at −80°C in 20% glycerol. Strains were cultured in YPAD medium (yeast extract, peptone, and 2% dextrose) supplemented with 40 μg/ml adenine and 80 μg/ml uridine. To start the in vitro evolution experiment, the FLC-susceptible progenitor clinical isolates SC5314 and P75063 were plated for single colonies on YPAD + 2% agar plates directly from the −80°C. Plates were left to incubate for 48 h in a 30°C incubator.

In Vitro Evolution Experiment
The FLC-susceptible progenitor clinical isolates (SC5314, P75063, and FH1) were plated for single colonies onto YPAD + 2% glucose agar medium and incubated for 48 h at 30°C. Twelve single colonies from each progenitor isolate were selected at random and suspended in 1 ml of sterile liquid YPAD medium and incubated overnight at 30°C. After growth overnight, each single colony liquid suspension was diluted 1:1000 and used to start four independent lineages, defined as treatment groups (YPAD only, YPAD + 1 μg/ml FLC, YPAD + 8 μg/ml FLC, and YPAD + 64 μg/ml FLC) in deep-well 96-well plates. Plates were sealed with Breathe EASIER tape (Electron Microscopy Sciences) and placed in a humidified chamber for 72 h at 30°C. Every 72 h, cells were carefully resuspended and transferred to fresh medium containing the same concentration of FLC to a final cell dilution of 1:1000. In total, 10 transfers were conducted. After the final transfer, cells were collected for storage at −80°C, genomic DNA isolation, and for phenotypic analyses.

Microdilution MIC and SMG Assays
The microwell broth dilution assay was used to determine both the MIC 50 and SMG for each lineage put through the in vitro evolution experiment. Lineages evolved in FLC during the in vitro evolution experiment were inoculated from a −80°C freezer into fresh liquid YPAD medium supplemented with 1 μg/ml FLC and grown for 16 h in a 30°C shaking incubator. Lineages evolved in the absence of FLC during the in vitro evolution experiment were inoculated into fresh liquid YPAD (with no added FLC) and grown for 16 h in a 30°C shaking incubator. From these cultures, cells were inoculated into a 96-well plate containing 180 μl of a 0.5X dextrose YPAD medium with a 2-fold serial dilution of FLC or a no-drug control to a final cell dilution of 1:1000 and a final volume of 200 μl. Cells were incubated at 30°C in a humidified chamber and OD 600 readings were taken at both 24 and 48 h post inoculation; cells were resuspended by pipette prior to reading. The MIC 50 of each lineage was determined to be the concentration of FLC at which ≥50% of growth was inhibited when compared with the no-drug control. Supra-MIC growth (SMG) was calculated by taking the average OD 600 value of the wells above the 24 h MIC 50 at 48 h and dividing by the OD 600 in the no-drug control well (Rosenberg et al. 2018).

Growth Curve Analysis
For growth curve analysis, cells were cultured overnight in 3 mL YPAD liquid culture, diluted to an OD 600 value of 0.1 and aliquoted into a 96-well plate with either YPAD or YPAD + 1 μg/ml FLC. Cultures were grown at 30°C with constant dual-orbital agitation in a Biotek Epoch plate reader, and OD measurements were taken every 15 min Summary statistics for growth curves, including the fitted logistic models and areas under the fitted curve, were calculated using default parameters with the R package The 8 μg/ml treatment group had a significantly higher median MIC than the three other treatment groups. Lineages exposed to 8 μg/ml and 64 μg/ml FLC had a significantly higher SMG than lineages exposed to 0 μg/ml FLC. (B) Whole-genome sequence data plotted as in figure 3 with chromosome copy number (y-axis, 1-4 copies) as a function of chromosome position (x-axis, Chr1-ChrR). The ploidy of all FH1-evolved lineages remained 2N by flow cytometry (Table 2). FH1 lineages are grouped by drug treatment (0 μg/ml FLC, 1 μg/ml FLC, 8 μg/ml FLC, and 64 μg/ml FLC). All lineages evolved at 8 μg/ml FLC acquired an extra copy (trisomy) of the same Chr5 homolog (Chr5B). (C) Frequency and type of singlenucleotide changes identified in the 48 replicate lineages.
Evolution of Antifungal Resistance or Tolerance is Dependent on Drug Concentration · https://doi.org/10.1093/molbev/msad009MBE Growthcurver (Sprouffske and Wagner 2016). Significant differences were determined using the area under the curve for each lineage and treatment (three replicates in each group, P < 0.05, ANOVA with Tukey post-hoc test).

Visualization of Aneuploid Chromosomes
Aneuploidies were visualized using the Yeast Mapping Analysis Pipeline (YMAP, v1.0) (Abbey et al. 2014). BAM files aligned to the SC5314 reference genome (A21-s02-m09-r08) were uploaded to YMAP and read depth was determined and plotted as a function of chromosome position. Read depth was corrected for both chromosome-end bias and GC-content.

Identification of LOH Events
Preliminary identification of LOH events was conducted using aligned Illumina reads and YMAP plots generated above. YMAP plots for each lineage (e.g., SC5314 A 0 , A 1 , A 8 , A 64 ) were visually compared with each other to look for regions underwent homozygosis, based on heterozygosity in the other three lineages at the same region. Approximate LOH boundaries were identified from YMAP GBrowse allele ratio tracks, and confirmed by visual inspection in IGV (IGV, v2.8.2) (Thorvaldsdottir et al. 2013). An LOH event was defined as a transition from at least four consecutive heterozygous alleles to four consecutive homozygous alleles and vice versa. Heterozygous alleles had an alternate allele frequency of at least 20%, with at least a read depth of 10, and forward and reverse strands supporting the alternate allele. The position of the first and last informative homozygous alleles (LOH breakpoints) was recorded along with the lineage in which this occurred and the length of the LOH event (last informative allele position minus the first informative allele position, Table 3). If the LOH breakpoints were within 5000 bp of the start or end of the chromosome sequence, the breakpoint was considered to be to the telomere end, and the first or last nucleotide position of the chromosome was recorded. If both breakpoints were to the ends of a chromosome, the LOH event was denoted as a wholechromosome LOH.
Identification of de novo variants (variants that arose during the evolution experiment, and therefore were likely not present in a significant proportion of the initial progenitor population) required additional filtering steps. First, variants were kept if they satisfied the following criteria: at least five reads contained the alternate allele; at least one read in the forward and reverse direction contained the variant; the variant was not located in a repetitive region, such as the MRS or ribosomal subunits (Todd and Selmecki 2020). Then, variants present in the initial progenitor were defined as those that fit either criteria: A) an identical variant found in at least half of the sequenced lineages of the no drug control experiments (i.e., 3/6 lineages for SC5314 and P75063, or 6/12 lineages for FH1); or B) variants that were present in all four drug treatments of a given lineage. These progenitor variants were removed from the de novo mutation list. All variants were verified visually using the Integrative Genomics Viewer (IGV, v2.8.2) (Thorvaldsdottir et al. 2013). Mutations were then annotated with gene descriptions from the CGD (Table 3).
Gene Ontology Analysis GO Term Finder analysis (Boyle et al. 2004) was conducted on the set of all genes with SNVs, from drug-treated (1, 8, 64 μg/ml FLC) strains with progenitors SC5314 or P75063 for Process, Function, and Component Ontology, on the CGD (accessed August 31, 2022). The only significant Todd et al. · https://doi.org/10.1093/molbev/msad009 MBE cluster detected is for the GO term long-chain fatty acid metabolic process (P < 0.05, hypergeometric distribution with Bonferroni Correction). Similar analyses were conducted with the set of all genes with SNVs from drugtreated (1, 8, 64 μg/ml FLC) lineages with progenitors SC5314, P75063, and FH1, but no significant terms were identified.

Supplementary material
Supplementary data are available at Molecular Biology and Evolution online.